flan
29afcd00b1
torch's multi-threaded CPU forward pass intermittently raised SIGILL under CPU contention on the deployment host; the collector swallowed it as non-fatal, so that cycle silently computed no new embeddings. Pinning inference to a single thread avoids the racy parallel kernel and removes multi-threaded reduction nondeterminism, so recomputed vectors are bit-reproducible. Bump 0.8.2 -> 0.8.3: a vector recomputed after this change can differ from a pre-0.8.3 one at ~1e-6 and move a borderline article across the cluster threshold, which may shift a rating.
56 lines
1.3 KiB
TOML
56 lines
1.3 KiB
TOML
[project]
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name = "tiltmeter"
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version = "0.8.3"
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description = "Auditable, reproducible political-lean ratings for news outlets"
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readme = "README.md"
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requires-python = ">=3.13"
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license = { text = "MIT" }
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authors = [{ name = "flan", email = "flan@arch.fyi" }]
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dependencies = [
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"feedparser>=6.0",
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"trafilatura>=1.12",
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"pyyaml>=6.0",
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"sentence-transformers>=3.0",
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# torch is transitive via sentence-transformers, but must be a direct
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# dependency for the pytorch-cpu index pin below to apply (uv resolves
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# tool.uv.sources for direct dependencies only) — otherwise the lock
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# pulls CUDA torch and the Docker image balloons to ~7GB
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"torch>=2.6",
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"scikit-learn>=1.5",
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"numpy>=2.0",
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"requests>=2.32",
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]
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[project.scripts]
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tiltmeter = "tiltmeter.cli:main"
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[dependency-groups]
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dev = [
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"pytest>=8.0",
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"ruff>=0.8",
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"textstat>=0.7",
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]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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# CPU-only torch: reproducibility runs on any machine, no GPU nondeterminism
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[[tool.uv.index]]
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name = "pytorch-cpu"
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url = "https://download.pytorch.org/whl/cpu"
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explicit = true
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[tool.uv.sources]
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torch = { index = "pytorch-cpu" }
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[tool.hatch.build.targets.wheel]
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packages = ["src/tiltmeter"]
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[tool.ruff]
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line-length = 100
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target-version = "py313"
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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